The present invention relates generally to producing pattern defect inspection systems for wafers, masks, and reticles. More particularly, the present invention relates to a method of filtering optical images to improve the sensitivity to “real” defects on inspected samples.
In a conventional optical inspection system, defects are detected by subtracting a reference image from a test image and low-pass filtering the difference image. The test image is an optical image of an area on the photomask. The reference image may be an optical image of a similar area on an identical die or on the same die or a rendered design database. The grayscale residues, i.e., portions of the difference image having a value other than zero, represent defects in the inspected sample.
“Real” defects must be isolated from spurious or “false” defects. Conventional methods are susceptible to the generation of false defects since defects will be detected wherever the test image does not match the reference image. Thus, false defects will be detected whenever incomplete subtraction occurs and residues exceed a specified threshold. To minimize false defect occurrences, stringent requirements are imposed on the mechanical stability of the inspection tool. For example, high frequency vibrations must be minimized to prevent alignment mismatches which will result in numerous errors. The algorithms for aligning and filtering the test and reference images must ensure precise matches. Even rendered images may produce numerous false defects if the algorithm for matching the rendered image from the design database file is not strictly controlled. Rendering database reference images to match the test images are particularly difficult for low-k1 reticles which are used in state-of-the-art optical lithography.
Filtering of the difference image is performed to increase the defect signal relative to the background residue, which would be zero if the images were identical. Conventional techniques perform low-pass filtering operation on the difference image to reduce the quantity of pattern noise, i.e., false defects arising from the factors discussed above. Low pass filtering has the effect of smoothing out the difference image. Defects are then determined as the grayscale residues exceeding a specified threshold. False defects counts may be reduced by raising the thresholds for defect detection, but raising the threshold may mask real defects.
More sophisticated filtering techniques are available to enhance the defect's signal to noise ratio relative to the background in the difference image. For example, Fourier transform techniques are useful for filtering out periodic (repeating) signals. However, defects in wafers and other samples may be embedded in a background that is non-stationary, i.e., one whose frequency is not constant. In such cases Fourier transform methods have limited utility. Many kinds of background patterns may be observed on masks, for example, including stationary or non-stationary types. They may be non-repeating. What is needed is a mechanism for improving the signal from a defect relative to various types of background noise in the detection of defects on photomasks, reticles, or wafers.